6,392 research outputs found
Visuelle Analyse großer Partikeldaten
Partikelsimulationen sind eine bewährte und weit verbreitete numerische Methode in der Forschung und Technik. Beispielsweise werden Partikelsimulationen zur Erforschung der Kraftstoffzerstäubung in Flugzeugturbinen eingesetzt. Auch die Entstehung des Universums wird durch die Simulation von dunkler Materiepartikeln untersucht. Die hierbei produzierten Datenmengen sind immens. So enthalten aktuelle Simulationen Billionen von Partikeln, die sich über die Zeit bewegen und miteinander interagieren. Die Visualisierung bietet ein großes Potenzial zur Exploration, Validation und Analyse wissenschaftlicher Datensätze sowie der zugrundeliegenden
Modelle. Allerdings liegt der Fokus meist auf strukturierten Daten mit einer regulären Topologie. Im Gegensatz hierzu bewegen sich Partikel frei durch Raum und Zeit. Diese Betrachtungsweise ist aus der Physik als das lagrange Bezugssystem bekannt. Zwar können Partikel aus dem lagrangen in ein reguläres eulersches Bezugssystem, wie beispielsweise in ein uniformes Gitter, konvertiert werden. Dies ist bei einer großen Menge an Partikeln jedoch mit einem erheblichen Aufwand verbunden. Darüber hinaus führt diese Konversion meist zu einem Verlust der Präzision bei gleichzeitig erhöhtem Speicherverbrauch. Im Rahmen dieser Dissertation werde ich neue Visualisierungstechniken erforschen, welche speziell auf der lagrangen Sichtweise basieren. Diese ermöglichen eine effiziente und effektive visuelle Analyse großer Partikeldaten
Preferential concentration of inertial sub-kolmogorov particles. The roles of mass loading of particles, Stokes and Reynolds numbers
Turbulent flows laden with inertial particles present multiple open questions
and are a subject of great interest in current research. Due to their higher
density compared to the carrier fluid, inertial particles tend to form high
concentration regions, i.e. clusters, and low concentration regions, i.e.
voids, due to the interaction with the turbulence. In this work, we present an
experimental investigation of the clustering phenomenon of heavy sub-Kolmogorov
particles in homogeneous isotropic turbulent flows. Three control parameters
have been varied over significant ranges: ,
and volume fraction . The scaling of clustering characteristics, such as the distribution
of Vorono\"i areas and the dimensions of cluster and void regions, with the
three parameters are discussed. In particular, for the polydispersed size
distributions considered here, clustering is found to be enhanced strongly
(quasi-linearly) by and noticeably (with a square-root
dependency) with , while the cluster and void sizes, scaled with the
Kolmogorov lengthscale , are driven primarily by . Cluster
length scales up to , measured
at the highest , while void length
scaled also with is typically two times larger ().
The lack of sensitivity of the above characteristics to the Stokes number lends
support to the "sweep-stick" particle accumulation scenario. The non-negligible
influence of the volume fraction, however, is not considered by that model and
can be connected with collective effects
Flow networks: A characterization of geophysical fluid transport
We represent transport between different regions of a fluid domain by flow
networks, constructed from the discrete representation of the Perron-Frobenius
or transfer operator associated to the fluid advection dynamics. The procedure
is useful to analyze fluid dynamics in geophysical contexts, as illustrated by
the construction of a flow network associated to the surface circulation in the
Mediterranean sea. We use network-theory tools to analyze the flow network and
gain insights into transport processes. In particular we quantitatively relate
dispersion and mixing characteristics, classically quantified by Lyapunov
exponents, to the degree of the network nodes. A family of network entropies is
defined from the network adjacency matrix, and related to the statistics of
stretching in the fluid, in particular to the Lyapunov exponent field. Finally
we use a network community detection algorithm, Infomap, to partition the
Mediterranean network into coherent regions, i.e. areas internally well mixed,
but with little fluid interchange between them.Comment: 16 pages, 15 figures. v2: published versio
Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible.
Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code.Dissertation/ThesisDoctoral Dissertation Physics 201
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